bdm::mgamma Class Reference

Gamma random walk. More...

#include <exp_family.h>

List of all members.

Public Member Functions

 mgamma ()
 Constructor.
void set_parameters (double k, const vec &beta0)
 Set value of k.
void condition (const vec &val)
 Update iepdf so that it represents this mpdf conditioned on rvc = cond This function provides convenient reimplementation in offsprings.
void from_setting (const Setting &set)
egammae ()
 access function to iepdf
vec samplecond (const vec &cond)
 Reimplements samplecond using condition().
double evallogcond (const vec &val, const vec &cond)
 Reimplements evallogcond using condition().
virtual vec evallogcond_m (const mat &Dt, const vec &cond)
 Efficient version of evallogcond for matrices.
virtual vec evallogcond_m (const Array< vec > &Dt, const vec &cond)
 Efficient version of evallogcond for Array<vec>.
virtual mat samplecond_m (const vec &cond, int N)
 Efficient version of samplecond.
virtual string to_string ()
 This method returns a basic info about the current instance.
virtual void to_setting (Setting &set) const
 This method save all the instance properties into the Setting structure.
virtual void validate ()
 This method TODO.
Access to attributes
const RV_rv () const
const RV_rvc () const
int dimension () const
int dimensionc ()
Connection to other objects
void set_rvc (const RV &rvc0)
void set_rv (const RV &rv0)
bool isnamed ()

Protected Member Functions

void set_ep (epdf &iepdf)
 set internal pointer ep to point to given iepdf
void set_ep (epdf *iepdfp)
 set internal pointer ep to point to given iepdf

Protected Attributes

double k
 Constant $k$.
vec & _beta
 cache of iepdf.beta
egamma iepdf
 Internal epdf used for sampling.
int dimc
 dimension of the condition
RV rvc
 random variable in condition


Detailed Description

Gamma random walk.

Mean value, $\mu$, of this density is given by rvc . Standard deviation of the random walk is proportional to one $k$-th the mean. This is achieved by setting $\alpha=k$ and $\beta=k/\mu$.

The standard deviation of the walk is then: $\mu/\sqrt(k)$.


Member Function Documentation

void bdm::mgamma::from_setting ( const Setting &  set  )  [inline, virtual]

Create Gamma density with conditional mean value

\[ f(rv|rvc) = \Gamma(k, k/rvc) \]

from structure

                  class = 'mgamma';
                  beta = [...];          // vector of initial alpha
                  k = 1.1;               // multiplicative constant k
                  rv = RV({'name'})      // description of RV
                  rvc = RV({'name'})     // description of RV in condition

Reimplemented from bdm::mpdf.

References bdm::UI::get(), k, and set_parameters().


The documentation for this class was generated from the following files:

Generated on Wed Oct 7 17:34:48 2009 for mixpp by  doxygen 1.5.9